{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\J.PARK\Dropbox\Discrimination Project_for me\Organizational Diversity\2023 Version_Merging\FINAL\CFA_2015.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 8 Aug 2024, 13:22:09
{txt}
{com}. 
. import delimited "C:\Users\J.PARK\Dropbox\DISCRIMINATION PROJECT\FEVS\FEVS_2010-2019\evs2015_PRDF.csv"
{res}{txt}(encoding automatically selected: ISO-8859-1)
{res}{text}(99 vars, 421,748 obs)

{com}. drop if q17=="X"
{txt}(18,409 observations deleted)

{com}. drop if q17==""
{txt}(3,183 observations deleted)

{com}. drop if q37=="X"
{txt}(18,916 observations deleted)

{com}. drop if q37==""
{txt}(9,135 observations deleted)

{com}. drop if q38=="X"
{txt}(17,175 observations deleted)

{com}. drop if q38==""
{txt}(3,368 observations deleted)

{com}. drop if q15=="X"
{txt}(3,080 observations deleted)

{com}. drop if q15==""
{txt}(1,468 observations deleted)

{com}. drop if q22=="X"
{txt}(12,702 observations deleted)

{com}. drop if q22==""
{txt}(2,205 observations deleted)

{com}. drop if q25=="X"
{txt}(7,767 observations deleted)

{com}. drop if q25==""
{txt}(1,850 observations deleted)

{com}. drop if q33=="X"
{txt}(6,454 observations deleted)

{com}. drop if q33==""
{txt}(3,127 observations deleted)

{com}. drop if q48==.
{txt}(2,492 observations deleted)

{com}. drop if q49==.
{txt}(1,071 observations deleted)

{com}. destring q17, replace
{txt}q17: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q37, replace
{txt}q37: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q38, replace
{txt}q38: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q15, replace
{txt}q15: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q22, replace
{txt}q22: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q25, replace
{txt}q25: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q33, replace
{txt}q33: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. drop if q55=="X"
{txt}(8,185 observations deleted)

{com}. drop if q55==""
{txt}(4,671 observations deleted)

{com}. drop if q45=="X"
{txt}(8,316 observations deleted)

{com}. drop if q45==""
{txt}(1,215 observations deleted)

{com}. drop if q34=="X"
{txt}(4,695 observations deleted)

{com}. drop if q34==""
{txt}(1,107 observations deleted)

{com}. destring q55, replace
{txt}q55: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q45, replace
{txt}q45: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q34, replace
{txt}q34: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. drop if dsuper=="X"
{txt}(0 observations deleted)

{com}. drop if dsuper==""
{txt}(10,204 observations deleted)

{com}. drop if dsex=="X"
{txt}(0 observations deleted)

{com}. drop if dsex==""
{txt}(5,744 observations deleted)

{com}. drop if dminority==.
{txt}(8,477 observations deleted)

{com}. gen minority = 0 if dminority==2
{txt}(88,588 missing values generated)

{com}. replace minority = 1 if dminority==1
{txt}(88,588 real changes made)

{com}. gen gender = 1 if dsex == "B"
{txt}(137,971 missing values generated)

{com}. replace gender = 0 if dsex == "A"
{txt}(137,971 real changes made)

{com}. gen supervisor = 1 if dsuper == "B" 
{txt}(192,978 missing values generated)

{com}. replace supervisor = 0 if dsuper == "A"
{txt}(192,978 real changes made)

{com}. 
. svyset [pweight=postwt]

{txt}Sampling weights:{col 19}{res}postwt
             {txt}VCE:{col 19}{res}linearized
     {txt}Single unit:{col 19}{res}missing
        {txt}Strata 1:{col 19}<one>
 Sampling unit 1:{col 19}<observations>
           FPC 1:{col 19}<zero>
{p2colreset}{...}

{com}. 
. svy linearized : sem (JUSTICE -> DISTRIBUTIVE, ) (JUSTICE -> PROCEDURAL, ) (JUSTICE -> INTERPERSONAL, ) (DISTRIBUTIVE -> q22, ) (DISTRIBUTIVE -> q25, ) (DISTRIBUTIVE -> q33, ) (PROCEDURAL -> q15, ) (PROCEDURAL -> q17, ) (PROCEDURAL -> q37, ) (PROCEDURAL -> q38, )(INTERPERSONAL -> q48, ) (INTERPERSONAL -> q49, ), standardized latent(JUSTICE DISTRIBUTIVE PROCEDURAL INTERPERSONAL ) nocapslatent
{res}{txt}(running {bf:sem} on estimation sample)
{res}
{txt}{col 1}Survey: Structural equation model{col 52}{lalign 15:Number of obs}{col 67} = {res}{ralign 9:256,732}
{txt}{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 7:1}{txt}{col 52}{lalign 15:Population size}{col 67} = {res}{ralign 9:1,087,291}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 7:256,732}{txt}{col 52}{lalign 15:Design df}{col 67} = {res}{ralign 9:256,731}

{p 0 7}{space 1}{text:( 1)}{space 1} [q22]DISTRIBUTIVE = 1{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [q15]PROCEDURAL = 1{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [q48]INTERPERSONAL = 1{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [DISTRIBUTIVE]JUSTICE = 1{p_end}
{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}  Linearized
{col 1}       Standardized{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural         {col 21}{txt}{c |}
{space 2}{col 3}DISTRIBUTIVE     {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .8471857{col 33}{space 2} .0019375{col 44}{space 1}  437.25{col 53}{space 3}0.000{col 61}{space 4} .8433881{col 74}{space 3} .8509832
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}PROCEDURAL       {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .9865395{col 33}{space 2} .0019836{col 44}{space 1}  497.34{col 53}{space 3}0.000{col 61}{space 4} .9826516{col 74}{space 3} .9904273
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}INTERPERSONAL    {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .6961291{col 33}{space 2} .0022746{col 44}{space 1}  306.04{col 53}{space 3}0.000{col 61}{space 4}  .691671{col 74}{space 3} .7005873
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Measurement        {col 21}{txt}{c |}
{space 2}{col 3}q22              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .8457448{col 33}{space 2} .0013587{col 44}{space 1}  622.45{col 53}{space 3}0.000{col 61}{space 4} .8430817{col 74}{space 3} .8484079
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.340331{col 33}{space 2} .0048093{col 44}{space 1}  486.62{col 53}{space 3}0.000{col 61}{space 4} 2.330904{col 74}{space 3} 2.349757
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q25              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .8334855{col 33}{space 2} .0014748{col 44}{space 1}  565.16{col 53}{space 3}0.000{col 61}{space 4}  .830595{col 74}{space 3}  .836376
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.458165{col 33}{space 2} .0053103{col 44}{space 1}  462.91{col 53}{space 3}0.000{col 61}{space 4} 2.447757{col 74}{space 3} 2.468573
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q33              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .7157583{col 33}{space 2} .0018985{col 44}{space 1}  377.01{col 53}{space 3}0.000{col 61}{space 4} .7120372{col 74}{space 3} .7194793
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.163484{col 33}{space 2} .0039416{col 44}{space 1}  548.89{col 53}{space 3}0.000{col 61}{space 4} 2.155758{col 74}{space 3} 2.171209
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q15              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .6155166{col 33}{space 2} .0026807{col 44}{space 1}  229.61{col 53}{space 3}0.000{col 61}{space 4} .6102625{col 74}{space 3} .6207706
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.234874{col 33}{space 2} .0092327{col 44}{space 1}  350.37{col 53}{space 3}0.000{col 61}{space 4} 3.216779{col 74}{space 3}  3.25297
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q17              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2}  .761914{col 33}{space 2} .0018812{col 44}{space 1}  405.01{col 53}{space 3}0.000{col 61}{space 4} .7582269{col 74}{space 3} .7656011
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  2.90648{col 33}{space 2} .0076915{col 44}{space 1}  377.88{col 53}{space 3}0.000{col 61}{space 4} 2.891405{col 74}{space 3} 2.921555
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q37              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .8348911{col 33}{space 2} .0015831{col 44}{space 1}  527.37{col 53}{space 3}0.000{col 61}{space 4} .8317883{col 74}{space 3}  .837994
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.664935{col 33}{space 2} .0063964{col 44}{space 1}  416.63{col 53}{space 3}0.000{col 61}{space 4} 2.652399{col 74}{space 3} 2.677472
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q38              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2}  .813243{col 33}{space 2} .0017454{col 44}{space 1}  465.95{col 53}{space 3}0.000{col 61}{space 4} .8098222{col 74}{space 3} .8166639
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.225061{col 33}{space 2} .0092441{col 44}{space 1}  348.88{col 53}{space 3}0.000{col 61}{space 4} 3.206942{col 74}{space 3} 3.243179
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q48              {col 21}{c |}
{space 6}INTERPERSONAL {c |}{col 21}{res}{space 2} .9406846{col 33}{space 2} .0011979{col 44}{space 1}  785.30{col 53}{space 3}0.000{col 61}{space 4} .9383369{col 74}{space 3} .9430324
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.717844{col 33}{space 2} .0114465{col 44}{space 1}  324.80{col 53}{space 3}0.000{col 61}{space 4} 3.695409{col 74}{space 3} 3.740279
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q49              {col 21}{c |}
{space 6}INTERPERSONAL {c |}{col 21}{res}{space 2} .9165882{col 33}{space 2}  .001286{col 44}{space 1}  712.76{col 53}{space 3}0.000{col 61}{space 4} .9140677{col 74}{space 3} .9191086
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 4.052617{col 33}{space 2} .0136639{col 44}{space 1}  296.59{col 53}{space 3}0.000{col 61}{space 4} 4.025836{col 74}{space 3} 4.079398
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}var(e.q22){c |}{col 21}{res}{space 2} .2847157{col 33}{space 2} .0022983{col 61}{space 4} .2802466{col 74}{space 3} .2892562
{txt}{space 10}var(e.q25){c |}{col 21}{res}{space 2}  .305302{col 33}{space 2} .0024584{col 61}{space 4} .3005214{col 74}{space 3} .3101586
{txt}{space 10}var(e.q33){c |}{col 21}{res}{space 2} .4876901{col 33}{space 2} .0027178{col 61}{space 4} .4823924{col 74}{space 3}  .493046
{txt}{space 10}var(e.q15){c |}{col 21}{res}{space 2} .6211394{col 33}{space 2}    .0033{col 61}{space 4}  .614705{col 74}{space 3} .6276411
{txt}{space 10}var(e.q17){c |}{col 21}{res}{space 2}  .419487{col 33}{space 2} .0028666{col 61}{space 4}  .413906{col 74}{space 3} .4251434
{txt}{space 10}var(e.q37){c |}{col 21}{res}{space 2} .3029568{col 33}{space 2} .0026434{col 61}{space 4} .2978197{col 74}{space 3} .3081824
{txt}{space 10}var(e.q38){c |}{col 21}{res}{space 2} .3386358{col 33}{space 2} .0028388{col 61}{space 4} .3331173{col 74}{space 3} .3442457
{txt}{space 10}var(e.q48){c |}{col 21}{res}{space 2} .1151124{col 33}{space 2} .0022536{col 61}{space 4}  .110779{col 74}{space 3} .1196153
{txt}{space 10}var(e.q49){c |}{col 21}{res}{space 2} .1598661{col 33}{space 2} .0023574{col 61}{space 4} .1553118{col 74}{space 3}  .164554
{txt}{space 1}var(e.DISTRIBUTIVE){c |}{col 21}{res}{space 2} .2822765{col 33}{space 2} .0032829{col 61}{space 4} .2759148{col 74}{space 3} .2887848
{txt}{space 3}var(e.PROCEDURAL){c |}{col 21}{res}{space 2} .0267399{col 33}{space 2} .0039139{col 61}{space 4}  .020071{col 74}{space 3} .0356246
{txt}var(e.INTERPERSONAL){c |}{col 21}{res}{space 2} .5154042{col 33}{space 2} .0031668{col 61}{space 4} .5092345{col 74}{space 3} .5216487
{txt}{space 8}var(JUSTICE){c |}{col 21}{res}{space 2}        1{col 33}{space 2}        .{col 61}{space 4}        .{col 74}{space 3}        .
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estat gof, stats(all)
{res}
{txt}{hline 21}{c TT}{hline 54}
{lalign 21:Fit statistic}{c |}      Value   Description
{hline 21}{c +}{hline 54}
{lalign 21:Size of residuals}{c |}
{ralign 20:SRMR} {c |} {res}{ralign 10:     0.040}{txt}   Standardized root mean squared residual
{ralign 20:CD} {c |} {res}{ralign 10:     0.976}{txt}   Coefficient of determination
{hline 21}{c BT}{hline 54}
{p 0 2 2 75}Note: model was fit with{txt} svy: prefix; only stats(residuals) valid.{p_end}

{com}. 
. predict justice, latent(JUSTICE)
{res}{txt}
{com}. 
. svy linearized : sem (DIVERSITY -> q34, ) (DIVERSITY -> q45, ) (DIVERSITY -> q55, ), standardized latent(DIVERSITY) nocapslatent
{res}{txt}(running {bf:sem} on estimation sample)
{res}
{txt}{col 1}Survey: Structural equation model{col 52}{lalign 15:Number of obs}{col 67} = {res}{ralign 9:256,732}
{txt}{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 7:1}{txt}{col 52}{lalign 15:Population size}{col 67} = {res}{ralign 9:1,087,291}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 7:256,732}{txt}{col 52}{lalign 15:Design df}{col 67} = {res}{ralign 9:256,731}

{p 0 7}{space 1}{text:( 1)}{space 1} [q34]DIVERSITY = 1{p_end}
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}  Linearized
{col 1} Standardized{col 15}{c |} Coefficient{col 27}  std. err.{col 39}      t{col 47}   P>|t|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Measurement  {col 15}{txt}{c |}
{space 2}{col 3}q34        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .6907205{col 27}{space 2} .0027203{col 38}{space 1}  253.91{col 47}{space 3}0.000{col 55}{space 4} .6853888{col 68}{space 3} .6960522
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.279038{col 27}{space 2} .0089099{col 38}{space 1}  368.02{col 47}{space 3}0.000{col 55}{space 4} 3.261575{col 68}{space 3} 3.296501
{space 2}{txt}{hline 12}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q45        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .7462925{col 27}{space 2} .0026213{col 38}{space 1}  284.70{col 47}{space 3}0.000{col 55}{space 4} .7411547{col 68}{space 3} .7514303
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.534983{col 27}{space 2} .0103557{col 38}{space 1}  341.36{col 47}{space 3}0.000{col 55}{space 4} 3.514686{col 68}{space 3}  3.55528
{space 2}{txt}{hline 12}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q55        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .8100018{col 27}{space 2} .0024468{col 38}{space 1}  331.05{col 47}{space 3}0.000{col 55}{space 4} .8052063{col 68}{space 3} .8147974
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.360333{col 27}{space 2} .0096053{col 38}{space 1}  349.84{col 47}{space 3}0.000{col 55}{space 4} 3.341507{col 68}{space 3} 3.379159
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}var(e.q34){c |}{col 15}{res}{space 2} .5229052{col 27}{space 2} .0037579{col 55}{space 4} .5155914{col 68}{space 3} .5303228
{txt}{space 4}var(e.q45){c |}{col 15}{res}{space 2} .4430475{col 27}{space 2} .0039126{col 55}{space 4} .4354449{col 68}{space 3} .4507828
{txt}{space 4}var(e.q55){c |}{col 15}{res}{space 2}  .343897{col 27}{space 2} .0039637{col 55}{space 4} .3362153{col 68}{space 3} .3517543
{txt}var(DIVERSITY){c |}{col 15}{res}{space 2}        1{col 27}{space 2}        .{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estat gof, stats(all)
{res}
{txt}{hline 21}{c TT}{hline 54}
{lalign 21:Fit statistic}{c |}      Value   Description
{hline 21}{c +}{hline 54}
{lalign 21:Size of residuals}{c |}
{ralign 20:SRMR} {c |} {res}{ralign 10:     0.000}{txt}   Standardized root mean squared residual
{ralign 20:CD} {c |} {res}{ralign 10:     0.803}{txt}   Coefficient of determination
{hline 21}{c BT}{hline 54}
{p 0 2 2 75}Note: model was fit with{txt} svy: prefix; only stats(residuals) valid.{p_end}

{com}. 
. predict diversity, latent(DIVERSITY)
{res}{txt}
{com}. 
. keep if agency =="AM" | agency =="ED" | agency =="DN" | agency =="HU" | agency =="ST" | agency =="EP"  | agency =="FC" | agency =="GS" | agency =="NN" | agency =="NU" | agency =="OM" | agency =="SE" | agency =="SZ" | plevel1 =="DD34" | plevel1 =="DD10" | plevel1 =="DD63" | plevel1 =="DD35" | plevel1 =="DD04" | plevel1 =="DD07" | plevel1 =="DD27" | plevel1 =="DD60" | plevel2 =="AG1001" | plevel2 =="AG0101" | plevel2 =="AG0401" | plevel2 =="AG0501" | plevel2 =="AG0502" |plevel2 =="AG1501" | plevel1 =="CM03"  | plevel1 =="CM08" | plevel1 =="CM09" | plevel1 =="CM14" | plevel1 =="HE04" | plevel1 =="HE05" | plevel1 =="HE06" | plevel1 =="HE08" | plevel1 =="HE09" | plevel1 =="HE10" | plevel1 =="HE12" |plevel1 =="HS04" | plevel1 =="HS14" | plevel1 =="HS01" | plevel1 =="HS03" | plevel1 =="HS02" | plevel1 =="HS06" | plevel1 =="HS12" | plevel1 =="DJ15" | plevel1 =="DJ03" | plevel1 =="DJEA" | plevel1 =="DJ09" | plevel1 =="DJ02" | plevel1 =="DJ08" | plevel1 =="DL03" | agency =="AF" | agency =="AR" | plevel1 =="IN03" | plevel1 =="IN01" | plevel1 =="IN02" | plevel1 =="IN07" | plevel1 =="IN05" | plevel1 =="IN06" | agency =="NV" | plevel1 =="TRFS" | plevel1 =="TR93" | plevel1 =="TRAJ" | plevel1 =="TD03" | plevel1 =="TD04" | plevel1 =="VA03" | plevel1 =="VA02"
{txt}(38,471 observations deleted)

{com}. 
. svy linearized : sem (JUSTICE -> DISTRIBUTIVE, ) (JUSTICE -> PROCEDURAL, ) (JUSTICE -> INTERPERSONAL, ) (DISTRIBUTIVE -> q22, ) (DISTRIBUTIVE -> q25, ) (DISTRIBUTIVE -> q33, ) (PROCEDURAL -> q15, ) (PROCEDURAL -> q17, ) (PROCEDURAL -> q37, ) (PROCEDURAL -> q38, )(INTERPERSONAL -> q48, ) (INTERPERSONAL -> q49, ), standardized latent(JUSTICE DISTRIBUTIVE PROCEDURAL INTERPERSONAL ) nocapslatent
{res}{txt}(running {bf:sem} on estimation sample)
{res}
{txt}{col 1}Survey: Structural equation model{col 52}{lalign 15:Number of obs}{col 67} = {res}{ralign 9:218,261}
{txt}{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 7:1}{txt}{col 52}{lalign 15:Population size}{col 67} = {res}{ralign 9:1,009,871}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 7:218,261}{txt}{col 52}{lalign 15:Design df}{col 67} = {res}{ralign 9:218,260}

{p 0 7}{space 1}{text:( 1)}{space 1} [q22]DISTRIBUTIVE = 1{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [q15]PROCEDURAL = 1{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [q48]INTERPERSONAL = 1{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [DISTRIBUTIVE]JUSTICE = 1{p_end}
{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}  Linearized
{col 1}       Standardized{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural         {col 21}{txt}{c |}
{space 2}{col 3}DISTRIBUTIVE     {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .8451174{col 33}{space 2} .0020664{col 44}{space 1}  408.99{col 53}{space 3}0.000{col 61}{space 4} .8410674{col 74}{space 3} .8491674
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}PROCEDURAL       {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .9884265{col 33}{space 2} .0021166{col 44}{space 1}  466.98{col 53}{space 3}0.000{col 61}{space 4}  .984278{col 74}{space 3} .9925751
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}INTERPERSONAL    {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2}  .695535{col 33}{space 2} .0024231{col 44}{space 1}  287.04{col 53}{space 3}0.000{col 61}{space 4} .6907857{col 74}{space 3} .7002843
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Measurement        {col 21}{txt}{c |}
{space 2}{col 3}q22              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .8447991{col 33}{space 2} .0014511{col 44}{space 1}  582.20{col 53}{space 3}0.000{col 61}{space 4} .8419551{col 74}{space 3} .8476431
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.334596{col 33}{space 2} .0050749{col 44}{space 1}  460.03{col 53}{space 3}0.000{col 61}{space 4} 2.324649{col 74}{space 3} 2.344543
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q25              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .8333786{col 33}{space 2} .0015724{col 44}{space 1}  529.99{col 53}{space 3}0.000{col 61}{space 4} .8302967{col 74}{space 3} .8364606
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.451886{col 33}{space 2} .0056041{col 44}{space 1}  437.52{col 53}{space 3}0.000{col 61}{space 4} 2.440902{col 74}{space 3}  2.46287
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q33              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .7145862{col 33}{space 2} .0020257{col 44}{space 1}  352.76{col 53}{space 3}0.000{col 61}{space 4} .7106159{col 74}{space 3} .7185566
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.155269{col 33}{space 2} .0041519{col 44}{space 1}  519.11{col 53}{space 3}0.000{col 61}{space 4} 2.147132{col 74}{space 3} 2.163407
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q15              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .6130397{col 33}{space 2} .0028577{col 44}{space 1}  214.52{col 53}{space 3}0.000{col 61}{space 4} .6074387{col 74}{space 3} .6186407
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.234865{col 33}{space 2} .0098082{col 44}{space 1}  329.81{col 53}{space 3}0.000{col 61}{space 4} 3.215641{col 74}{space 3} 3.254089
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q17              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .7606281{col 33}{space 2} .0020068{col 44}{space 1}  379.02{col 53}{space 3}0.000{col 61}{space 4} .7566947{col 74}{space 3} .7645614
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.910863{col 33}{space 2} .0081999{col 44}{space 1}  354.99{col 53}{space 3}0.000{col 61}{space 4} 2.894791{col 74}{space 3} 2.926934
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q37              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .8337436{col 33}{space 2} .0016931{col 44}{space 1}  492.43{col 53}{space 3}0.000{col 61}{space 4} .8304251{col 74}{space 3} .8370621
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.666291{col 33}{space 2} .0068022{col 44}{space 1}  391.97{col 53}{space 3}0.000{col 61}{space 4} 2.652959{col 74}{space 3} 2.679623
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q38              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .8111465{col 33}{space 2} .0018675{col 44}{space 1}  434.36{col 53}{space 3}0.000{col 61}{space 4} .8074863{col 74}{space 3} .8148067
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.230128{col 33}{space 2} .0098574{col 44}{space 1}  327.68{col 53}{space 3}0.000{col 61}{space 4} 3.210807{col 74}{space 3} 3.249448
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q48              {col 21}{c |}
{space 6}INTERPERSONAL {c |}{col 21}{res}{space 2} .9404422{col 33}{space 2} .0012798{col 44}{space 1}  734.84{col 53}{space 3}0.000{col 61}{space 4} .9379338{col 74}{space 3} .9429506
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  3.71424{col 33}{space 2} .0121168{col 44}{space 1}  306.54{col 53}{space 3}0.000{col 61}{space 4} 3.690491{col 74}{space 3} 3.737989
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q49              {col 21}{c |}
{space 6}INTERPERSONAL {c |}{col 21}{res}{space 2}  .916106{col 33}{space 2} .0013725{col 44}{space 1}  667.49{col 53}{space 3}0.000{col 61}{space 4}  .913416{col 74}{space 3}  .918796
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 4.056154{col 33}{space 2} .0145332{col 44}{space 1}  279.10{col 53}{space 3}0.000{col 61}{space 4} 4.027669{col 74}{space 3} 4.084638
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}var(e.q22){c |}{col 21}{res}{space 2} .2863145{col 33}{space 2} .0024517{col 61}{space 4} .2815493{col 74}{space 3} .2911603
{txt}{space 10}var(e.q25){c |}{col 21}{res}{space 2} .3054801{col 33}{space 2} .0026209{col 61}{space 4} .3003861{col 74}{space 3} .3106604
{txt}{space 10}var(e.q33){c |}{col 21}{res}{space 2} .4893665{col 33}{space 2} .0028951{col 61}{space 4}  .483725{col 74}{space 3} .4950738
{txt}{space 10}var(e.q15){c |}{col 21}{res}{space 2} .6241823{col 33}{space 2} .0035037{col 61}{space 4} .6173527{col 74}{space 3} .6310875
{txt}{space 10}var(e.q17){c |}{col 21}{res}{space 2}  .421445{col 33}{space 2} .0030529{col 61}{space 4} .4155037{col 74}{space 3} .4274712
{txt}{space 10}var(e.q37){c |}{col 21}{res}{space 2} .3048717{col 33}{space 2} .0028233{col 61}{space 4}  .299388{col 74}{space 3} .3104558
{txt}{space 10}var(e.q38){c |}{col 21}{res}{space 2} .3420414{col 33}{space 2} .0030296{col 61}{space 4} .3361547{col 74}{space 3} .3480311
{txt}{space 10}var(e.q48){c |}{col 21}{res}{space 2} .1155685{col 33}{space 2} .0024071{col 61}{space 4} .1109455{col 74}{space 3} .1203841
{txt}{space 10}var(e.q49){c |}{col 21}{res}{space 2} .1607498{col 33}{space 2} .0025146{col 61}{space 4}  .155896{col 74}{space 3} .1657547
{txt}{space 1}var(e.DISTRIBUTIVE){c |}{col 21}{res}{space 2} .2857766{col 33}{space 2} .0034926{col 61}{space 4} .2790125{col 74}{space 3} .2927047
{txt}{space 3}var(e.PROCEDURAL){c |}{col 21}{res}{space 2}  .023013{col 33}{space 2} .0041842{col 61}{space 4} .0161141{col 74}{space 3} .0328655
{txt}var(e.INTERPERSONAL){c |}{col 21}{res}{space 2} .5162311{col 33}{space 2} .0033708{col 61}{space 4} .5096665{col 74}{space 3} .5228801
{txt}{space 8}var(JUSTICE){c |}{col 21}{res}{space 2}        1{col 33}{space 2}        .{col 61}{space 4}        .{col 74}{space 3}        .
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estat gof, stats(all)
{res}
{txt}{hline 21}{c TT}{hline 54}
{lalign 21:Fit statistic}{c |}      Value   Description
{hline 21}{c +}{hline 54}
{lalign 21:Size of residuals}{c |}
{ralign 20:SRMR} {c |} {res}{ralign 10:     0.040}{txt}   Standardized root mean squared residual
{ralign 20:CD} {c |} {res}{ralign 10:     0.979}{txt}   Coefficient of determination
{hline 21}{c BT}{hline 54}
{p 0 2 2 75}Note: model was fit with{txt} svy: prefix; only stats(residuals) valid.{p_end}

{com}. 
. predict justice2, latent (JUSTICE)
{res}{txt}
{com}. 
. svy linearized : sem (DIVERSITY -> q34, ) (DIVERSITY -> q45, ) (DIVERSITY -> q55, ), standardized latent(DIVERSITY) nocapslatent
{res}{txt}(running {bf:sem} on estimation sample)
{res}
{txt}{col 1}Survey: Structural equation model{col 52}{lalign 15:Number of obs}{col 67} = {res}{ralign 9:218,261}
{txt}{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 7:1}{txt}{col 52}{lalign 15:Population size}{col 67} = {res}{ralign 9:1,009,871}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 7:218,261}{txt}{col 52}{lalign 15:Design df}{col 67} = {res}{ralign 9:218,260}

{p 0 7}{space 1}{text:( 1)}{space 1} [q34]DIVERSITY = 1{p_end}
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}  Linearized
{col 1} Standardized{col 15}{c |} Coefficient{col 27}  std. err.{col 39}      t{col 47}   P>|t|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Measurement  {col 15}{txt}{c |}
{space 2}{col 3}q34        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .6877306{col 27}{space 2} .0029067{col 38}{space 1}  236.61{col 47}{space 3}0.000{col 55}{space 4} .6820337{col 68}{space 3} .6934276
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.285046{col 27}{space 2} .0095083{col 38}{space 1}  345.49{col 47}{space 3}0.000{col 55}{space 4} 3.266409{col 68}{space 3} 3.303682
{space 2}{txt}{hline 12}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q45        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .7470282{col 27}{space 2} .0028022{col 38}{space 1}  266.59{col 47}{space 3}0.000{col 55}{space 4}  .741536{col 68}{space 3} .7525203
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.531981{col 27}{space 2} .0109748{col 38}{space 1}  321.83{col 47}{space 3}0.000{col 55}{space 4}  3.51047{col 68}{space 3} 3.553491
{space 2}{txt}{hline 12}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q55        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .8096254{col 27}{space 2} .0026131{col 38}{space 1}  309.84{col 47}{space 3}0.000{col 55}{space 4} .8045038{col 68}{space 3} .8147469
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.368734{col 27}{space 2}  .010265{col 38}{space 1}  328.18{col 47}{space 3}0.000{col 55}{space 4} 3.348614{col 68}{space 3} 3.388853
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}var(e.q34){c |}{col 15}{res}{space 2} .5270266{col 27}{space 2}  .003998{col 55}{space 4} .5192486{col 68}{space 3} .5349211
{txt}{space 4}var(e.q45){c |}{col 15}{res}{space 2} .4419489{col 27}{space 2} .0041866{col 55}{space 4}  .433819{col 68}{space 3} .4502312
{txt}{space 4}var(e.q55){c |}{col 15}{res}{space 2} .3445068{col 27}{space 2} .0042312{col 55}{space 4} .3363127{col 68}{space 3} .3529005
{txt}var(DIVERSITY){c |}{col 15}{res}{space 2}        1{col 27}{space 2}        .{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estat gof, stats(all)
{res}
{txt}{hline 21}{c TT}{hline 54}
{lalign 21:Fit statistic}{c |}      Value   Description
{hline 21}{c +}{hline 54}
{lalign 21:Size of residuals}{c |}
{ralign 20:SRMR} {c |} {res}{ralign 10:     0.000}{txt}   Standardized root mean squared residual
{ralign 20:CD} {c |} {res}{ralign 10:     0.802}{txt}   Coefficient of determination
{hline 21}{c BT}{hline 54}
{p 0 2 2 75}Note: model was fit with{txt} svy: prefix; only stats(residuals) valid.{p_end}

{com}. 
. predict diversity2, latent (DIVERSITY)
{res}{txt}
{com}. 
. sum justice, detail

                   {txt}Factor score (JUSTICE)
{hline 61}
      Percentiles      Smallest
 1%    {res} -2.14987      -2.228955
{txt} 5%    {res}-1.603196      -2.228955
{txt}10%    {res}-1.157961      -2.228955       {txt}Obs         {res}    218,261
{txt}25%    {res}-.4200252      -2.228955       {txt}Sum of wgt. {res}    218,261

{txt}50%    {res} .2081096                      {txt}Mean          {res} .0622199
                        {txt}Largest       Std. dev.     {res} .8309863
{txt}75%    {res} .6311445       1.353888
{txt}90%    {res}  1.08691       1.353888       {txt}Variance      {res} .6905383
{txt}95%    {res} 1.272177       1.353888       {txt}Skewness      {res}-.6669487
{txt}99%    {res} 1.353888       1.353888       {txt}Kurtosis      {res} 2.968694
{txt}
{com}. 
. sum justice2, detail

                   {txt}Factor score (JUSTICE)
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.142976       -2.22026
{txt} 5%    {res}-1.596031       -2.22026
{txt}10%    {res}-1.152022       -2.22026       {txt}Obs         {res}    218,261
{txt}25%    {res}-.4155061       -2.22026       {txt}Sum of wgt. {res}    218,261

{txt}50%    {res} .2127427                      {txt}Mean          {res} .0657792
                        {txt}Largest       Std. dev.     {res} .8291769
{txt}75%    {res} .6345139       1.351963
{txt}90%    {res} 1.088378       1.351963       {txt}Variance      {res} .6875343
{txt}95%    {res} 1.272084       1.351963       {txt}Skewness      {res}-.6688261
{txt}99%    {res} 1.351963       1.351963       {txt}Kurtosis      {res} 2.970068
{txt}
{com}. 
. sum diversity, detail

                  {txt}Factor score (DIVERSITY)
{hline 61}
      Percentiles      Smallest
 1%    {res}-1.935633      -1.935633
{txt} 5%    {res} -1.25635      -1.935633
{txt}10%    {res}-.8393415      -1.935633       {txt}Obs         {res}    218,261
{txt}25%    {res}-.3002441      -1.935633       {txt}Sum of wgt. {res}    218,261

{txt}50%    {res} .1993399                      {txt}Mean          {res} .0398044
                        {txt}Largest       Std. dev.     {res}  .656045
{txt}75%    {res} .4761628       .9757468
{txt}90%    {res} .9757468       .9757468       {txt}Variance      {res}  .430395
{txt}95%    {res} .9757468       .9757468       {txt}Skewness      {res}-.8393383
{txt}99%    {res} .9757468       .9757468       {txt}Kurtosis      {res} 3.653738
{txt}
{com}. 
. sum diversity2, detail

                  {txt}Factor score (DIVERSITY)
{hline 61}
      Percentiles      Smallest
 1%    {res}-1.924494      -1.924494
{txt} 5%    {res}-1.251188      -1.924494
{txt}10%    {res}-.8302673      -1.924494       {txt}Obs         {res}    218,261
{txt}25%    {res}-.2984885      -1.924494       {txt}Sum of wgt. {res}    218,261

{txt}50%    {res} .1975576                      {txt}Mean          {res} .0419242
                        {txt}Largest       Std. dev.     {res} .6530358
{txt}75%    {res} .4769515       .9729975
{txt}90%    {res} .9729975       .9729975       {txt}Variance      {res} .4264557
{txt}95%    {res} .9729975       .9729975       {txt}Skewness      {res}-.8399348
{txt}99%    {res} .9729975       .9729975       {txt}Kurtosis      {res} 3.654158
{txt}
{com}. 
. corr justice justice2
{txt}(obs=218,261)

             {c |}  justice justice2
{hline 13}{c +}{hline 18}
     justice {c |}{res}   1.0000
    {txt}justice2 {c |}{res}   1.0000   1.0000

{txt}
{com}. 
. corr diversity diversity2 
{txt}(obs=218,261)

             {c |} divers~y divers~2
{hline 13}{c +}{hline 18}
   diversity {c |}{res}   1.0000
  {txt}diversity2 {c |}{res}   1.0000   1.0000

{txt}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\J.PARK\Dropbox\Discrimination Project_for me\Organizational Diversity\2023 Version_Merging\FINAL\CFA_2015.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 8 Aug 2024, 13:23:09
{txt}{.-}
{smcl}
{txt}{sf}{ul off}